The Effect of Unitization Strategy on Age-related Associative Memory Deficit
Bibliographic record
Abstract
<p>The associative memory deficits observed in healthy older adults have been demonstrated to be at least partially driven by age-related declines in recollection-based memory processes (Old & Naveh-Benjamin, 2008). Parks and Yonelinas (2015) suggested that unitization – a memory strategy that synthesizes two previously unrelated objects into a new single entity which represents characteristics of both – could improve young adults’ associative memory performance by promoting familiarity-based, but not recollection-based, memory processes. This dissertation aimed to examine whether this unitization strategy could promote familiarity in older adults and subsequently improve their associative memory performance. Experiment 1 was a pilot study in which twenty young (aged 18-23) and 20 older adults (aged 65-89) were instructed to self-generate unitization mnemonics (compound definition, i.e., a definition for the compound that unitizes the two words) and a non-unitization strategy (sentence frame, i.e., a sentence that connects the two words). Results showed that although older adults took longer than their younger counterparts, they were better at generating mnemonics following both types of strategy instruction. In Experiment 2, thirty-six young and 36 older adults completed an associative memory task. During encoding, they studied word pairs, each with a sentence frame or a compound definition mnemonic as generated in Experiment 1. Then their memory for items as well as for pairs was assessed using a remember/know/new paradigm. Results indicated that for both age groups, familiarity increased in the unitization relative to the non-unitization condition. However, the increase in familiarity did not help older adults improve their associative memory in the same way as observed in the young adult group within the same experiment. Experiment 3 adopted an intentional encoding paradigm and a within-subject design. Thirty-two older adults studied word pairs using both sentence frame and compound definition strategy in two random-ordered blocks. Replicating Experiment 2, the unitization strategy boosted the level of familiarity-based retrieval but did not lead to better associative memory performance in older adults. Taken together, the results of this dissertation suggest that although unitization increased familiarity for older adults, it did not mitigate their associative memory deficits more effectively than a non-unitization strategy.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".